Role Summary The AI Architect is responsible for designing end-to-end AI/ML and GenAI solution architectures that translate business requirements into scalable, production-grade systems. This role bridges technical strategy and delivery, working closely with AI/ML Engineers, GenAI Engineers, and client stakeholders to ensure solutions are robust, secure, and aligned with enterprise architecture standards.

Key Responsibilities

- Design and own end-to-end architecture for AI/ML and GenAI solutions, including data pipelines, model serving, orchestration, and integration layers
- Evaluate and select appropriate frameworks, cloud services, and toolchains (e.g., Azure AI, AWS, GCP, LLM providers, vector databases)
- Define architecture patterns for RAG systems, agentic workflows, MLOps/LLMOps pipelines, and model governance
- Partner with client stakeholders and internal delivery teams to translate business problems into technical solution designs
- Establish best practices for scalability, security, cost optimization, and responsible AI/model risk management
- Conduct architecture reviews and provide technical guidance to engineering teams during implementation
- Create solution blueprints, reference architectures,



and technical documentation for proposals and delivery
- Stay current with emerging AI/ML technologies and assess their applicability to client and internal use cases
- Support pre-sales activities including solutioning, effort estimation, and technical proposal development

Required Qualifications

- Bachelor's/Master's degree in Computer Science, Engineering, or related field
- 8+ years in software/data architecture, with 3+ years focused on AI/ML or GenAI solution design
- Robust hands-on background in ML system design, cloud architecture (Azure/AWS/GCP), and MLOps practices
- Experience architecting LLM-based applications (RAG, agents, fine-tuning, prompt orchestration)
- Familiarity with data engineering, APIs, microservices, and enterprise integration patterns
- Strong communication skills for client-facing architecture discussions

Preferred

- Relevant cloud/AI certifications (e.g., Azure AI Engineer/Solutions Architect)
- Experience in a consulting or professional services environment
- Exposure to model governance, responsible AI frameworks, and cost/performance optimization at scale

📌 AI Architect (Chennai)
🏢 Agilisium Consulting
📍 Chennai